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Comparing methods to detect cellular proteins on the surface of HIV-1 virions

2024· article· en· W4405098626 on OpenAlexafffund
Deepa Chaphekar, Claire Fernandes, Arvin Tejnarine Persaud, Christina Guzzo

Bibliographic record

VenueJournal of Virological Methods · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicHIV Research and Treatment
Canadian institutionsUniversity of Toronto
FundersNational Institutes of HealthUniversity of Toronto ScarboroughNational Institute of Allergy and Infectious DiseasesNatural Sciences and Engineering Research Council of CanadaInstitute of Infection and ImmunityCanadian Institutes of Health ResearchCanada Foundation for Innovation
KeywordsBiologyHuman immunodeficiency virus (HIV)VirologyComputational biologyVirusCell biology

Abstract

fetched live from OpenAlex

The surface of HIV-1 is embedded with numerous host-derived proteins. Characterizing these proteins can enhance knowledge of virus biology and potentially identify novel therapeutic targets. As many of these proteins are present in low abundance on virion surfaces, their identification can be hindered by inherent variables in the methods employed to detect them, including their varying assay sensitivities, sample processing, quantitative capacity, and experimental reproducibility. Here, we have compared the quantification of virion-incorporated proteins using conventional virus immunocapture assays and western blotting, alongside an emerging technique called flow virometry (FV). Using four different pseudovirus models that each express a human protein of interest (CD14, CD38, CD59 and CD162), we compared four experimental techniques for their ability to reliably quantify the incorporation of those four proteins onto virion surfaces. Our results shed light on the advantages and caveats of each technique for detecting virion-incorporated proteins and highlight the breadth in quantification for each technique under different experimental conditions. Protein detection with flow virometry provided distinct advantages as it enabled highly reproducible quantifications, had the lowest sample requirements and reagent costs, and minimal hands-on experimental time. We additionally highlight some important considerations in experimental design when studying virion-incorporated proteins, such as the effect of different antibody clones, assay incubation times, and contributions of extracellular vesicles. Most importantly, our data illustrate the importance of using a combination of orthogonal approaches to detect virus-associated proteins, to enable reliable and reproducible quantification that accounts for individual assay biases. • Virion-incorporated human proteins on the HIV-1 surface can impact virus biology. • Capture assays, western blot, and flow virometry can detect incorporated proteins. • Flow virometry yields highly reproducible, calibrated, quantitative results. • Capture assays yield semi-quantitative results, on virus particles specifically. • Western blotting yields semi-quantitative results, influenced by assay parameters. • Using assays in tandem enables reliable reporting of virion-incorporated proteins.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.783

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.105
GPT teacher head0.419
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2024
Admission routes2
Has abstractyes

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